Biological, Environmental, & Climate Sciences (BECS) Department Seminar
"Atmospheric Ice Formation: What can be Learned from Ice Nucleation Studies"
Presented by Daniel Knopf, Stony Brook University
Friday, April 17, 2015, 11:00 am — Conference Room, Bldg 815E
Ice formation represents one of the biggest challenges in atmospheric sciences for prediction of mixed-phase and cirrus clouds with subsequent consequences for the global radiative budget and hydrological cycle. The reasons for this are manifold: ice nucleation can occur via different pathways with each mechanism depending on the ambient thermodynamic conditions such as temperature and relative humidity; only a small fraction of particles nucleates ice as low as one in a million; the physicochemical complexity of ice nucleating particles (INPs); the ice nucleation efficiency of ambient particles. This seminar will introduce a multi-modal methodology approach allowing optical, micro-spectroscopy, and chemical imaging of individual identified field-collected and laboratory generated INPs active in immersion freezing and deposition ice nucleation. Ice formation pathways are studied for temperatures as low as 200 K covering typical atmospheric conditions. In the first part of this presentation a new model of immersion freezing will be presented. It is based on droplet water activity and accounts for INP surface area and nucleation time. Its application and implications for cloud modeling will be discussed. The second part is concerned with the unique ability to quantitatively characterize the individual INP among hundred thousands of particles not nucleating ice. These findings raise a new perspective on the parameters governing atmospheric ice nucleation. The data demonstrates that the INPs are not necessarily exceptional particles in comparison to the ambient population with regard to composition and mixing state. However, particle surface area, besides ice nucleation kinetics, may also constitute a crucial factor for our predictive understanding of the ice nucleation process. Lastly, a stochastic model is applied to re-analyze laboratory immersion freezing data demonstrating that statistically insufficient freezing experiment numbers and inaccurate estimates of INP s
Hosted by: Ernie Lewis
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